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Course in Reinforcement Learning (RL) + 8 ECTS Credits (Baremable in Oppositions*)

Add points to your scale with this training

Baremable course in oppositions and transfer competitions (consult the official bases)
Qualification valid as merit in public selective processes
Designed in accordance with current state regulations, R.D. 276/2007 (it is essential to consult the bases of your CC. AA.).

$303.00

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Duration

200 hours

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Credits

8 ECTS

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Language

Spanish

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No limit

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Agenda

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Credit your success

At the end of the course, you will obtain the accredited qualification

This is not just about learning, but also about accrediting your knowledge with the most important institutions in the sector:

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Course Qualification in Reinforcement Learning (RL) with 200 hours and 8 ECTS issued by UTAMED-Atlantic Mediterranean Technological University. * Course baremable in oppositions, always subject to the rules of the call, and current regional legislation.

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Learn from the best in your sector

ana belen salinas lozano

Graduate in Primary Education and Graduate in Psychopedagogy, with more than 20 years of experience in the non-regulated training sector. He has developed his career in the management and delivery of subsidized training, Vocational Training for Employment, professionalism certificates, training linked to program contracts and private training, both in person and online. His profile combines teaching experience and training management capacity in different contexts and program types.

Teaching experience:

Teacher in non-regulated training: Provision of subsidized training; Provision of Vocational Training for Employment; Provision of professional certificates; Delivery of training contracts program; Private training provision; In-person and online mode.

Professional experience:

Management of non-regulated training programs: Organization and coordination of training actions; Subsidized training management; Management of Vocational Training for Employment programs; Management of professional certificates; Management of training contracts, program and private training.

Professional skills:

Comprehensive management of subsidized training; Coordination of Vocational Training for Employment; Design and delivery of professional certificates; Training in person and online.

Graduate in Primary Education and Graduate in Psychopedagogy, with more than 20 years of experience in the non-regulated training sector. He has developed his career in the management and delivery of subsidized training, Vocational Training for Employment, professionalism certificates, training linked to program contracts and private training, both in person and online. His profile combines teaching experience and training management capacity in different contexts and program types.

Teaching experience:

Teacher in non-regulated training: Provision of subsidized training; Provision of Vocational Training for Employment; Provision of professional certificates; Delivery of training contracts program; Private training provision; In-person and online mode.

Professional experience:

Management of non-regulated training programs: Organization and coordination of training actions; Subsidized training management; Management of Vocational Training for Employment programs; Management of professional certificates; Management of training contracts, program and private training.

Professional skills:

Comprehensive management of subsidized training; Coordination of Vocational Training for Employment; Design and delivery of professional certificates; Training in person and online.

andrea carolina rojas zuluaga

Graduated in Early Childhood Education, with a Master in Culture of Peace, Conflicts, Education and Human Rights and a Master in Psychopedagogical Intervention. He develops his work as a teacher at the Faculty of Teaching of Educa Edtech Group. She has experience as an early childhood educator and as a manager of educational projects, integrating pedagogical approaches linked to psycho-pedagogical intervention, education in values and the promotion of educational environments based on the culture of peace.

Teaching experience:

Teacher — Educa Edtech Group: Development of training activities in the Faculty of Teaching.

Professional experience:

Children's educator. Educational project manager.

Professional skills:

Psychopedagogical intervention; early childhood education; Educational project management; Education in culture of peace and human rights.

Languages:

English B2.

Graduated in Early Childhood Education, with a Master in Culture of Peace, Conflicts, Education and Human Rights and a Master in Psychopedagogical Intervention. He develops his work as a teacher at the Faculty of Teaching of Educa Edtech Group. She has experience as an early childhood educator and as a manager of educational projects, integrating pedagogical approaches linked to psycho-pedagogical intervention, education in values and the promotion of educational environments based on the culture of peace.

Teaching experience:

Teacher — Educa Edtech Group: Development of training activities in the Faculty of Teaching.

Professional experience:

Children's educator. Educational project manager.

Professional skills:

Psychopedagogical intervention; early childhood education; Educational project management; Education in culture of peace and human rights.

Languages:

English B2.

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The Supervised Learning Course in ML is designed so that you acquire the necessary skills in a booming sector, where the demand for trained professionals does not stop growing. With this course you will be able to develop a solid foundation in regression, classification and model evaluation techniques, essential for any aspiring data scientist. You will learn from the fundamentals of machine learning to advanced methods such as neural networks and support vector machines, ensuring you are prepared to meet today's challenges in the world of work. This online course offers flexibility and accessibility, allowing you to progress at your own pace while becoming an expert in supervised learning.

Passing this course will allow you to take a leap in your career by orienting yourself towards the technological forefront and Artificial Intelligence. This specialization will allow you to make a difference in your work environment, acquiring the necessary skills to opt for positions such as Predictive Data Analyst, Machine Learning Engineering Assistant, Junior Artificial Intelligence Consultant or AI Model Analyst with greater guarantees. Finally, as it has university certification, this course represents an excellent baremable merit to climb positions in job boards, competitive examinations and transfer competitions in the public sector of new technologies and research. (Note: The recognition of this training is subject to the bases of the specific call and the regional legislation of the territory where you apply).

The Supervised Learning Course in ML prepares you to address complex data analysis problems using advanced machine learning techniques. With this training you will learn from data preparation and preprocessing to the application of regression and classification algorithms. You will master models such as decision trees and neural networks, evaluating their effectiveness with cross-validation, among other things.

The Supervised Learning Course in ML is aimed at professionals and graduates who wish to delve deeper into machine learning techniques. It covers everything from the introduction to supervised learning to the application of neural networks, including linear regression, decision trees and SVM, providing essential tools for data analysis and modeling. It is also a key training for those seeking to increase their score on the merit scale of competitions and transfer competitions. Thanks to its university nature, it is aimed at candidates who need to add decisive points in their call (subject to the contest rules and regional regulations).

- Understand the fundamentals of supervised learning in machine learning. - Learn to prepare and preprocess data for machine learning models. - Apply linear regression to solve prediction problems. - Use logistic regression in binary classification tasks. - Evaluate models using cross-validation techniques. - Implement decision trees and ensembles such as Random Forest. - Develop neural networks focused on supervised learning.

Course in Reinforcement Learning (RL) + 8 ECTS Credits (Baremable in Oppositions*)

$303.00

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Course in Reinforcement Learning (RL) + 8 ECTS Credits (Baremable in Oppositions*)

Agenda

At the end of the course, you will obtain the accredited qualification

Learn from the best in your sector

Course information

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